Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [ ]:
from plotly.offline import init_notebook_mode
import plotly.io as pio

import plotly.express as px
import geopandas as gpd

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [ ]:
#load data
df = px.data.gapminder()
df.head()
Out[ ]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [ ]:
#load data
df= px.data.gapminder()
df.head()

#Data visualization
df_2007= df.query('year==2007')

df_2007_new= df_2007.groupby("continent").sum()
df_2007_new= df_2007_new.reset_index()

fig= px.bar(df_2007_new, x="pop", y="continent", orientation= "h", color="continent") #, text="pop" could use this in end to see amount but this looks more pretty
fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [ ]:
fig.update_layout(barmode="stack", yaxis={"categoryorder":"total ascending"})

Question 3:¶

Add text to each bar that represents the population

In [ ]:
# YOUR CODE HERE
fig= px.bar(df_2007_new, x="pop", y="continent", orientation= "h", color="continent", text="pop") #, could use this in end to see amount but this looks more pretty
fig.update_layout(barmode="stack", yaxis={"categoryorder":"total ascending"})
fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [ ]:
df= px.data.gapminder()
fig= px.bar(df, x="pop", y="continent", orientation= "h", color="continent", animation_frame='year', hover_name="country" ,range_x=[0,4000000000],) #text="pop"
fig.update_layout(barmode="stack", yaxis={"categoryorder":"total ascending"})
fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [ ]:
df= px.data.gapminder()
fig= px.bar(df, x="pop", y="country", orientation= "h", color="continent", animation_frame='year', hover_name="country" ,range_x=[0,1400000000],) #text="pop"
fig.update_layout(barmode="stack", yaxis={"categoryorder":"total ascending"})
fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [ ]:
df= px.data.gapminder()
fig= px.bar(df, x="pop", y="country", orientation= "h", color="country", animation_frame='year', hover_name="country" ,range_x=[0,1400000000], height=1000) #text="pop"
fig.update_layout(barmode="stack", yaxis={"categoryorder":"total ascending"})
#fig["layout"].pop("updatemenus") # optional, drop animation buttons
fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [ ]:
df= px.data.gapminder()
fig= px.bar(df, x="pop", y="country", orientation= "h", color="country", animation_frame='year', hover_name="country" ,range_x=[0,1400000000]) 
fig.update_yaxes(range=[131.5, 141.5]) #based on trial an error to see which bar fits best
fig.update_layout(barmode="stack", yaxis={"categoryorder":"total ascending"})
fig.show()